Linking Google Analytics (GA) with Google Ads is essential for digital marketers who want to maximise campaign performance. When you connect Google Analytics 4 (GA4) or Universal Analytics (UA) to Google Ads, you unlock a full view of the customer journey – from on-site behaviour to ad clicks – and can leverage rich audience data for targeting.

GA captures how users interact with your site or app (e.g. product views, add-to-cart events, purchases), while Google Ads lets you act on that data with tailored ads. By linking these platforms, audience insights flow seamlessly into Google Ads, enabling powerful strategies like eCommerce remarketing and Google Ads audience targeting based on analytics-driven segments.

In short, linking GA and Google Ads bridges your analytics and advertising, improving ROI through more relevant ads and better conversion tracking.

How Audience Data Flows from GA4/UA to Google Ads

Once GA4 or UA is linked to Google Ads, the process of sharing audience data is largely automated. Here’s how it works:

• Account Linking: First, you establish a link between your GA property (GA4 or UA) and your Google Ads account. This can be done from either platform’s interface (e.g. in GA4 under Admin > Product Links > Google Ads Link, or in Google Ads under Tools > Linked accounts > GA4). After linking, make sure personalised advertising (Google Signals) is enabled in GA so that user data can be used for remarketing.

• Audience Creation in GA: In GA4, you use the Audience Builder to define specific groups of users based on conditions (and similarly in UA, you would create an audience/segment with conditions). For example, you might create an audience of “Added to Cart but Not Purchased” users by defining inclusion/exclusion conditions on events – e.g. include users who triggered an add_to_cart event but exclude those who had a purchase event. GA4’s audience builder is very flexible, allowing conditions on events, user properties, demographics, and even the sequence of actions. (In UA, audiences were also defined by conditions, though GA4’s event-driven model offers more granular options.)

• Automatic Export to Google Ads: When an audience is saved in GA4, it is automatically published to linked Google Ads accounts for use in campaigns. You do not need to manually import or sync; GA will continuously update the audience membership and push those changes to Google Ads. In UA, you similarly had the option to publish audiences to linked Ads accounts during audience setup. Essentially, once you create an audience in GA and the accounts are linked, that audience appears in Google Ads (usually within 24-48 hours). For example, after saving a GA4 audience called “All Purchasers,” it will show up in Google Ads Audience Manager as a list named “All Purchasers (GA4) – [Your Property Name]” ready to be targeted.

• Continuous Refresh: The audience lists stay updated as new users meet (or fail to meet) the criteria. When GA detects a user has entered or exited an audience segment, it updates the membership in Google Ads automatically. This ensures your Google Ads remarketing lists are always current, so your ads reach the right people at the right time.

Key Capabilities Unlocked by GA Audiences in Google Ads

Linking GA4/UA with Google Ads gives advertisers several powerful capabilities using Analytics audiences:

• Remarketing to High-Intent Users: Analytics audiences become remarketing lists in Google Ads. This means you can serve ads specifically to users who previously engaged with your site/app. For example, Google’s documentation notes you could re-engage users who left items in their carts or who bought one item but not a complementary item. By targeting past site visitors, you can run eCommerce remarketing campaigns (display ads, search ads, YouTube ads, etc.) to bring them back and complete desired actions (purchases, sign-ups, etc.). GA4 lets you define very granular segments (e.g., users who viewed product X or spent over $Y) for more personalised retargeting (often referred to as GA4 retargeting).

• Exclusions for Better Efficiency: You can also use GA audiences to exclude certain users from your campaigns. For instance, if you have an audience of “Customers (Purchasers)”, you might exclude them from a prospecting campaign focused on new customer acquisition. GA4’s audience builder has an Exclude function to remove subsets (e.g., include users who added to cart and exclude those who purchased). This way, your Google Ads budget isn’t spent on users who have already converted, or you can suppress ads to audiences who are not relevant, thereby improving ROI.

• Audience Combinations & Segmentation: In Google Ads, imported GA audiences can be combined with other Google Ads audience segments to refine targeting. For example, you could take a GA4 audience of users with >5 purchases and intersect it with Google Ads in-market segments (like “Luxury Shoppers”) to find high-value customers who fit a certain profile. You can layer demographics, interests, or behaviours on top of GA audiences to create super-targeted groups.

• “Similar Audiences” (Lookalikes): Historically, Google Ads could generate Similar Audiences (Google’s term for lookalike segments) based on your remarketing lists. If your GA audience list was large enough, Google would find new users with characteristics similar to those on your list. Note: Google has been evolving this feature (phasing out explicit “Similar audiences” in favour of optimised targeting as of 2023), but the core idea remains – linking GA provides seed data (your first-party audiences) that Google’s machine learning can use to expand reach to users who “look like” your converters or engaged visitors. In practice, this means you can find new potential customers who share behaviours with your GA-defined audience (for example, target people similar to your “high LTV customers” segment) using Google’s automated audience expansion.

• Advanced Bidding & Optimisation: GA-linked audiences can also feed into Google Ads bidding strategies. For instance, you might use GA4 audiences in target CPA or ROAS bidding by applying them as observation segments in search campaigns to adjust bids for valuable segments (e.g., bid higher for past engagers). Additionally, Performance Max and other campaign types use your audiences as signals – by providing GA4 audiences (like “recent site visitors” or “repeat buyers”) as audience signals, you help Google’s AI learn who is valuable to your business and optimise ads accordingly.

In summary, linking GA audiences empowers remarketing, precise targeting, audience exclusions, lookalike expansion, and smarter bidding in Google Ads – capabilities that boost campaign relevance and efficiency.

E-commerce Audience Strategies Using GA4 Audiences

For eCommerce businesses, GA4 audiences open up a world of targeting opportunities. Here are four key audience segments (with use-case strategies) you should build in GA4 and use in Google Ads:

1. Cart Abandoners

Who they are: Users who added products to their cart but did not complete the purchase. These are high-intent shoppers who dropped off at the last step.

How to define in GA4: Create an audience including users who triggered the add_to_cart or begin_checkout event, but exclude those who had the purchase event in the same time frame. GA4’s sequence or exclude filters can accomplish this (e.g., users who added to cart and did not purchase within X days). In Universal Analytics, you would similarly define a segment of “Added to cart = Yes AND Transactions = 0”.

Activation in Google Ads: Use this audience as a remarketing list in Google Ads Display campaigns or Performance Max. You can serve dynamic display ads showing the exact products left in the cart (via Google’s dynamic remarketing for retail) or offer an incentive (like “10% off items in your cart”). On Search, you could apply this list to run RLSA (Remarketing Lists for Search Ads) – for example, bid more aggressively when past cart abandoners search for your brand or products. Cart abandoners are prime targets for eCommerce remarketing because a well-timed ad can persuade them to finalise the purchase.

2. Product Viewers (Browsers)

Who they are: Users who viewed product detail pages or categories but did not add anything to the cart. They showed interest but didn’t take the next step.

How to define in GA4: Build an audience of users who triggered a view_item event (or viewed specific product pages) without a subsequent add_to_cart or purchase. For example, “Product viewers – include users who viewed item X or category Y, and exclude those who added to cart or purchased in the last 7 days.” You can narrow this to specific high-value products or simply all product page visitors with no purchase.

Activation in Google Ads: Target these users with Google Ads audience targeting on Display and YouTube to re-engage them. Dynamic remarketing ads can show the exact products they viewed (or related items). This works as a gentle reminder of the products they checked out. For Search campaigns, you might use this audience to adjust bids or show tailored ad copy when these users search again (e.g., “Still interested in [Product]? Come back for a special offer.”). Product viewers are higher in the funnel than cart abandoners, so your ads might focus on product benefits or limited-time offers to drive the next action (add to cart or purchase).

3. Repeat Purchasers (Loyal Customers)

Who they are: Customers who have made multiple purchases from your site (e.g., repeat buyers or subscribers).

How to define in GA4: GA4 allows you to create audiences based on purchase count or revenue. For instance, define an audience of users with purchase count ≥ 2 (you might use the metric “Transactions” in UA or an event count in GA4). GA4’s audience builder can include users who have completed the purchase event more than once, or you could use a condition like “LTV > 0 and purchases >=2”. In UA, you might use the “number of transactions > =2” condition.

Activation in Google Ads: These repeat purchasers are your loyal customers – use them wisely. In Google Ads, you might exclude them from general acquisition campaigns (since they’ve already converted) to save budget, or conversely, target them in loyalty or upsell campaigns. For example, create a special Google Ads campaign (Display or even Customer Match list if you have their info) to promote new products, accessories, or premium services to this group. Because they’ve bought before, they might respond well to cross-sell or upgrade offers. You can also use this audience as a seed for similar audience expansion (finding new users similar to your best customers). Even though Google’s similar segments are evolving, these loyal users’ data can inform GA4 retargeting strategies and Google’s automated targeting for new users.

4. High-Lifetime-Value Customers

Who they are: Users who have a high lifetime value (LTV) – they’ve spent above a certain threshold or are predicted to generate high revenue. These could overlap with repeat purchasers, but essentially, this segment focuses on big spenders or VIP customers.

How to define in GA4: You can approach this in a few ways:

• If you have customer lifetime value calculated (through your CRM or by summing GA4 purchase revenue per user), create an audience for users with total revenue > X (e.g., > $500 lifetime). GA4 doesn’t directly provide a “lifetime revenue” metric in the UI, but you can approximate it by using purchase events and parameters. Another approach is using Predictive Audiences in GA4. GA4 offers predictive metrics like predicted 28-day top spenders, which automatically identify the top ~5% of users expected to generate the most revenue in the next 28 days. support.google.com If your GA4 property has enough data (e.g., at least 1000 purchasers in 28 days), you might use Google’s Predicted LTV or high-value audience suggestions. (Note: UA did not have predictive audiences, so this is a GA4-only capability using Google’s machine learning.)

Activation in Google Ads: High-LTV users are valuable for both retention and insights. In Google Ads, you might target them with exclusive offers or loyalty programs (e.g., an ad campaign only visible to your VIP audience, promoting a premium membership or referral bonus). Alternatively, use them as a model for acquisition: input this audience into a Performance Max campaign as an audience signal, so Google’s AI can find new users who behave like your best customers. Even without explicitly using “similar audiences,” PMax and Display campaigns with optimised targeting will use that seed data to find lookalikes. Also consider excluding high-LTV users from discount-oriented campaigns to avoid cannibalising revenue (e.g., you might not want to show a “10% off for new customers” ad to someone who would purchase anyway at full price). The key is to treat high-LTV customers separately – they merit special marketing attention due to their impact on revenue.

GA4 vs UA: Differences in Audience Definitions and Export

Both Universal Analytics and Google Analytics 4 allow the creation of audiences for Google Ads, but there are some notable differences:

• Data Model & Criteria: UA was session-based and had some predefined metrics (like “Session Duration” or “Number of Sessions”) that could be used in audience definitions. GA4 is event-based and does not use the concept of sessions in the same way, so audiences are defined by user-scoped events and properties. For example, a UA audience might have used “Page views per session > 3” or “Session Duration > 2 min” – those don’t translate directly to GA4. In GA4, you’d focus on events (e.g., “viewed 3 pages” can be an event count condition). UA’s “Number of sessions” metric isn’t available in GA4, so you must recreate such audiences with GA4’s closest equivalent data points. Despite these differences, both platforms let you define audiences by user behaviour – GA4 just offers a more flexible, user-centric approach (and some UA metrics need new approaches in GA4).

• Audience Limits: GA4 allows up to 100 audiences per property (free GA4), whereas Universal Analytics (free version) had a lower limit (UA standard properties were limited to 20 audiences per property). GA4’s higher limit and new features (like the ability to duplicate audiences and use templates) provide more room to create niche segments. Both GA4 and UA allow unlimited audience destinations (you can share an audience with multiple linked Google Ads accounts).

• Predictive Audiences: A major new feature in GA4 is predictive audiences – segments that automatically include users likely to act (purchase or churn) based on machine learning. For example, GA4 can generate an audience of “predicted 7-day purchasers” or “predicted 28-day top spenders” using its AI models, which was not possible in UA. UA did have a feature called Smart Lists (which automatically built a remarketing list of users likely to convert), but it was less customizable than GA4’s predictive capabilities. For marketers, this means GA4 can natively create “lookahead” segments that you can target in Google Ads (e.g., target users who GA4 predicts are likely to purchase soon). However, predictive audiences require sufficient data volumes (e.g. thousands of conversions) to be eligible.

• Publishing/Export Process: In UA, when creating an audience, you explicitly choose which linked Google Ads (or other Google Marketing Platform products) to publish the audience to. GA4 simplifies this: any audience you create is automatically shared to all linked Ads accounts by default. From the user perspective, both achieve the same result – your audiences appear in Google Ads for use – but GA4’s auto-export means one less manual step. Additionally, GA4 immediately starts populating the audience from creation time onwards (no backfilling past users, similar to UA’s behaviour that audiences are not retroactive).

• Migrating from UA to GA4: Since UA is now sunset (as of July 2023, UA stopped processing new hits), any UA audiences you needed to be recreated in GA4. Google did automatically map some UA audiences to GA4 equivalents for Google Ads if your accounts were linked (to prevent campaigns from breaking). However, not all UA audiences can be auto-migrated (especially those based on custom dimensions or metrics). It’s best to manually rebuild important UA audiences in GA4 using the new interface. Keep in mind you cannot directly import UA audience data into GA4 – you have to define the conditions in GA4 anew.

In essence, GA4 provides more advanced audience-building tools (and predictive segments) compared to UA, but the fundamental concept – defining user groups and sharing them with Google Ads – remains consistent. The upgrade to GA4 is an opportunity to refine your audiences with event-based tracking and take advantage of new features not found in UA.

Tips for Building Effective eCommerce Audiences in GA4

Crafting the right audiences in GA4 can make or break your Google Ads remarketing success. Here are some practical tips for building high-performing eCommerce audiences in GA4:

• Leverage GA4 E-commerce Events: Make sure you’re tracking GA4’s recommended eCommerce events (view_item, add_to_cart, begin_checkout, purchase, etc.). These events provide the building blocks for audiences like cart abandoners, product viewers, etc. Use event conditions (including event count and value parameters) to create precise segments – e.g., an audience of users who triggered view_item on a specific product category, or users who fired add_to_cart at least 3 times (high engagement shoppers).

• Use Inclusion and Exclusion Logic: GA4’s audience builder allows combining conditions with AND/OR, and also using Exclude filters. Take advantage of this to refine audiences. For example, include users who purchased in the last 6 months AND have viewed a particular category, but exclude those who purchased in the last 7 days (to target recent browsers who haven’t bought very recently). This layering ensures your list focuses on the right users.

• Set Realistic Membership Durations: When you create an audience, you choose a membership duration (how long a user stays in the audience after qualifying). The default is 30 days, and you can go up to 540 days in GA4/Google Ads. Adjust this based on your buying cycle. For fast-moving products or quick purchase decisions, a shorter duration (e.g., 7 or 14 days for cart abandoners) can make your ads feel timely. For longer consideration products or high-LTV segments, use longer durations. However, avoid making it so long that your ads become irrelevant (e.g., someone who showed interest 500 days ago is likely stale, as the Search Engine Land article humorously notes).

• Exploit GA4’s Templates and Suggestions: GA4 provides pre-built suggested audiences for common scenarios (e.g. “Purchasers” is auto-created, “All Users” is auto-created). Use these as a starting point. For example, GA4 might suggest an audience like “7-day inactive users” or “Purchasers in last 30 days.” You can use or tweak these suggestions instead of building from scratch. Also, consider GA4’s Predictive Audiences if available (like “Likely 7-day purchaser” or “Predicted top spenders”) to get a head start on advanced segments – these can be powerful if your data volume qualifies.

• Test Different Time Windows: Often, you might want multiple versions of a similar audience with different time frames. For instance, “Cart Abandoners (7-day)” vs “Cart Abandoners (30-day)” – the 7-day list captures very recent abandoners (hot leads), whereas the 30-day is a bit broader. You can easily duplicate an audience in GA4 and just change the membership duration or time window condition. This lets you bid or message differently to users based on recency. Maybe you offer a bigger discount to the 30-day-old abandoners vs. a gentle nudge to the 7-day ones.

• Ensure Sufficient Audience Size: A brilliant audience is useless if it’s too small to target. Check the audience estimate in GA4’s builder (it shows how many users in the last 30 days meet the criteria). Google Ads also has minimum size requirements to serve ads: e.g., at least 100 active users in the last 30 days for Display, and 1,000 for Search/YouTube remarketing lists. If your audience is very niche and falls below these, consider broadening the conditions or extending the time window. On the flip side, if an audience is huge (e.g., “All Site Visitors”), you might want to refine it or use it in combination with other targeting to make it more effective.

• Mind Privacy and Consent: GA4 and Google Ads abide by privacy settings. Ensure you have Google Signals enabled and ads personalisation allowed, or else your audiences won’t be eligible for remarketing. Additionally, if users opt out (e.g., via consent management on your site), GA4 will exclude them from advertising features. Always comply with laws like GDPR – have user consent for remarketing and be transparent in your privacy policy about data usage. From a practical standpoint, this means the audience sizes you see may exclude some users who didn’t consent, and that’s expected behaviour.

• Track Performance and Refine: After activating audiences in campaigns, monitor their performance. Google Ads’ Audience Manager will show you the size and status of each list (e.g., “List size: 5,000 on Display Network”), and you can see how each audience performs in the campaign reports (CTR, conversion rate, etc.). Use this data to refine definitions. Maybe you find that “Viewed product X” isn’t converting well – perhaps those users need a different approach, or the segment is too broad. Continuously iterate: split audiences, adjust durations, or combine with other criteria as needed to improve results.

Activating GA4 Audiences in Google Ads Campaigns

Once your GA4 (or UA) audiences are linked and available in Google Ads, the next step is to activate them in campaigns. Here’s how to use those audiences across various Google Ads campaign types:

• Display Remarketing Campaigns: This is the classic use case – show display ads to your past site visitors. In Google Ads, create a Display campaign (or a Discovery or YouTube campaign similarly) and in the “Audiences” settings, add your GA-derived audience under “Your data”. For example, target the “Cart Abandoners – 14 days (GA4)” list. Design image ads or responsive display ads highlighting the products they left behind or using messaging tailored to their segment. Ensure you set the targeting to “Targeting” (not Observation) so that the ads are shown only to that audience (for a pure remarketing campaign). Display campaigns are excellent for visually reminding users of products (especially when combined with dynamic remarketing feeds for e-commerce).

• Search Ads (RLSA): You can use GA audiences in Search and Shopping campaigns through Remarketing Lists for Search Ads. In your Google Ads search campaign, go to Audiences, and add your GA4 audience, but typically set it to “Observation” mode if you want to bid adjust rather than restrict traffic. For instance, you might add the “All Visitors (GA4)” audience to a search campaign and bid +30% when someone who previously visited the site searches your keywords – because they’re more likely to convert. Alternatively, you can use “Targeting” mode with RLSA to show ads only to those on the list (commonly done for keywords that you normally wouldn’t bid on except for people who have engaged before). An example strategy: target broad keywords like “running shoes sale” only to your past site visitors (using your GA4 “Past 30-day Visitors” list) to capitalise on their prior familiarity with your brand. This way, you can expand reach on search without blowing the budget on cold audiences.

• Performance Max Campaigns: Performance Max (PMax) is Google’s AI-driven campaign type that runs across all channels. You can’t explicitly choose audiences to limit who sees PMax ads, but you can provide Audience Signals. Add your GA4 audiences as audience signals to hint to Google who is likely to convert. For example, for a PMax campaign focused on sales, include signals like “Purchasers (GA4)”, “High LTV Customers”, or “Product viewers”. PMax will then use those as a starting point to find new conversions (it doesn’t stick only to those users, but it learns from them). This accelerates the machine learning by telling it what kind of users are valuable. Also, if your goal is new customer acquisition, you can use your GA4 “All Purchasers” audience as an exclusion at the account level (via Audience Manager’s exclusion lists or using the PMax customer acquisition setting) so that PMax prioritises new users over existing customers. Keep in mind, PMax will largely automate targeting, but feeding it high-quality first-party data (like your GA audiences) can improve its outcomes significantly.

• Other Campaign Types: GA audiences can be used in Discovery campaigns (to show engaging native-style ads on Google’s Discover feed and Gmail to your remarketing lists) and in YouTube campaigns (to retarget viewers or site visitors with video ads). For YouTube, you might run a campaign showing a product demo video only to people who visited your product page but didn’t buy – a great way to re-engage them with rich content. Additionally, if you’re using Search Ads 360 or DV360 (Google’s enterprise tools), any GA4 audiences linked to Google Ads can usually be ported there as well. support.google.com The key is that once the audience is in Google Ads, it’s part of your marketing arsenal across Google’s channels.

When activating audiences, always align your ad creative and messaging with the audience’s intent and position in the funnel. A user who just abandoned a cart might need a nudge or incentive (highlight urgency or discounts), whereas a repeat customer might be more receptive to a loyalty reward or new arrivals.

Google Ads allows you to customise ads (even use IF functions in search ads or ad customizers) for known audiences – take advantage of that to speak directly to these segments. For example, a search ad could say “Welcome back! Get 15% off your next purchase” only for the repeat purchasers list (using Google Ads IF function for audience).

Limitations and Common Pitfalls

Finally, be aware of a few limitations and pitfalls when working with Google Analytics audiences and Google Ads:

• Audience Size & Eligibility: As mentioned, Google Ads imposes minimum list sizes for remarketing. If your GA4 audience is too small (e.g., a very tight segment or a new site with low traffic), Google Ads will show it as “List size too small” and you won’t serve ads to that group. Build audiences that are meaningful but also large enough to use. If necessary, broaden the criteria (e.g., use a 30-day instead of a 7-day window) to increase the size. Also note that GA4’s interface shows estimated users, but Google Ads will calculate the reachable cookies/users – those numbers can differ due to cookie restrictions, device overlap, etc.

• Time to Populate: GA4 audiences are not retroactive. They start collecting users from the moment you create them (or from the point of linking accounts if created earlier). It can take 24-48 hours for a new audience to accumulate members and appear in Google Ads. Don’t panic if you don’t see users immediately or if Google Ads initially shows a list size of 0 – that’s expected until data accrues. Plan ahead by creating key audiences well before you need to use them in campaigns.

• Google Signals and Consent: If you forget to enable Google Signals (ads personalisation) in GA4, your audiences won’t be eligible for ad targeting. Always double-check that your GA4 property has Google Signals active (with proper user consent management in place). In addition, iOS users who opt out via Apple’s ATT framework are excluded from Ads audiences by GA4 by default (GA4 cannot include those users in exported audiences due to privacy. This means if a chunk of your users are on iOS and have opted out, your remarketing lists will exclude them – something to be aware of when analysing performance.

• UA to GA4 Transition Issues: If you recently migrated to GA4 from UA, note that UA-based audiences are no longer updating. Ensure all your critical audiences are rebuilt in GA4. Google Ads may have auto-mapped some (if you didn’t opt out), but you should verify their performance. Some marketers experienced slight differences in audience definitions (due to GA4’s different tracking). Monitor how your GA4 audiences perform compared to the old UA ones and adjust if needed (for example, GA4 might count “Users” differently than UA did).

• Overlapping Audiences & Exclusions: Use exclusions carefully to avoid cutting out too many users. For example, if you exclude “Purchasers (All time)” from a campaign, ensure you have another strategy to reach those customers with appropriate messaging. Also, check that your audiences don’t have logic conflicts (GA4 will handle the logic, but you want to be sure you’re including the right people). The GA4 audience summary tool is handy for reviewing if your include/exclude conditions are capturing the intended users.

• Ad Fatigue for Remarketing: When running remarketing to GA4 audiences (especially small ones like cart abandoners), be mindful of frequency capping and ad fatigue. Seeing the same ad repeatedly can annoy users. Google Ads allows frequency capping on Display/Video campaigns – implement that for your audiences (e.g., max 3 impressions per day per user) to avoid overexposure, especially if the audience is small.

• Privacy and Policy Compliance: Both GA4 and Google Ads have policies regarding personally identifiable information (PII) and sensitive categories. Avoid creating audiences that might be considered sensitive categories (Google Ads disallows targeting on categories like health conditions, certain financial information, etc., if derived in certain ways). Generally, standard eCommerce audiences, like we discussed, are fine, but just ensure you’re not violating any policies. Also, ensure your site’s privacy policy discloses the use of Google Analytics and Google Ads remarketing, and that users have a way to opt out, to stay compliant.

By linking GA4 with Google Ads and following these strategies and precautions, you can fully harness Google Analytics 4 audiences for smarter targeting. In an eCommerce context, this integration enables laser-focused GA4 retargeting (like chasing those cart abandoners) and nuanced audience targeting that can significantly lift your marketing performance.

Use the flexibility of GA4’s audience definitions to match your business goals – whether it’s re-engaging lapsed shoppers, upselling loyal customers, or finding new buyers who resemble your best clients. With careful setup and a bit of creativity, GA4 and Google Ads together become a powerhouse combo for eCommerce remarketing and beyond, driving more conversions and higher ROI from your campaigns.

Sources

1. Google Analytics Help – Use Analytics audiences in Google Ads (support.google.comsupport.google.com)

2. Google Analytics Help – Create a remarketing audience (GA4) (support.google.comsupport.google.com)

3. Search Engine Land – How to leverage GA4 and Google Ads for better targeting (searchengineland.comsearchengineland.com)

4. Jordan Digital Marketing – Guide: Creating Google Ads Audiences through GA4 (jordandigitalmarketing.comjordandigitalmarketing.com)

5. Analytics Mania – GA4 Audiences: Import to Google Ads (analyticsmania.comanalyticsmania.com)

6. Analytics Mates – GA4 Audiences vs UA Audiences (analyticsmates.comanalyticsmates.com)

7. Google Ads Help – Audience list size requirements